{"id":19445156,"url":"https://github.com/akashkg03/facial-expression-image-classification","last_synced_at":"2026-04-28T12:36:09.330Z","repository":{"id":223973899,"uuid":"762056233","full_name":"Akashkg03/Facial-Expression-Image-Classification","owner":"Akashkg03","description":"This notebook involves to build a facial expression image classifier which categorizes facial expressions into one of seven emotions: anger, disgust, fear, happiness, sadness, surprise, and neutral.","archived":false,"fork":false,"pushed_at":"2024-02-23T02:29:21.000Z","size":11927,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-25T08:32:51.110Z","etag":null,"topics":["jupiter-notebook","numpy","pandas","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Akashkg03.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-02-23T01:58:54.000Z","updated_at":"2024-02-23T02:29:25.000Z","dependencies_parsed_at":null,"dependency_job_id":"18cd56c6-fb31-49a2-b788-6c4e9442d4ae","html_url":"https://github.com/Akashkg03/Facial-Expression-Image-Classification","commit_stats":null,"previous_names":["akashkg03/facial-expression-image-classification"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Akashkg03/Facial-Expression-Image-Classification","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akashkg03%2FFacial-Expression-Image-Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akashkg03%2FFacial-Expression-Image-Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akashkg03%2FFacial-Expression-Image-Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akashkg03%2FFacial-Expression-Image-Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Akashkg03","download_url":"https://codeload.github.com/Akashkg03/Facial-Expression-Image-Classification/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akashkg03%2FFacial-Expression-Image-Classification/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":285240542,"owners_count":27137943,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-11-19T02:00:05.673Z","response_time":65,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["jupiter-notebook","numpy","pandas","python"],"created_at":"2024-11-10T16:09:32.069Z","updated_at":"2025-11-19T12:03:16.070Z","avatar_url":"https://github.com/Akashkg03.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Facial-Expression-Image-Classification\n### Problem Statement.\n- The objective of this project was to develop a machine learning model capable of classifying facial expressions in images into one of seven emotion categories: anger, disgust, fear, happiness, sadness, surprise, and neutral.\n  \n### Approach\nThe approach involved the following steps:\n1. Imported necessary libraries for data processing and model building.\n2. Data preparation, including loading the dataset and preprocessing.\n3. Feature extraction to convert the image into numerical features.\n4. Model Trained using a classification algorithm.\n5. Evaluated model's performance using appropriate metrics.\n   \n### Results:\nAchieved a accuracy of 97.67% on the test dataset, indicating the model's ability to accurately classify images.\n\n### Technologies Used:\nPython, pandas, scikit-learn, Jupyter Notebook.\n\n### Skills Demonstrated:\nData preprocessing, feature extraction, classification modeling, model evaluation.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakashkg03%2Ffacial-expression-image-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fakashkg03%2Ffacial-expression-image-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakashkg03%2Ffacial-expression-image-classification/lists"}